Simultaneous magnetic resonance and positron emission tomography provides an opportunity to measure brain haemodynamics and metabolism in a single scan session, and to identify brain activations from multimodal measurements in response to external stimulation. However, there are few analysis methods available for jointly analyzing the simultaneously acquired blood-oxygen-level dependent functional MRI (fMRI) and 18-F-fluorodeoxyglucose functional PET (fPET) datasets. In this work, we propose a new multimodality concatenated ICA (mcICA) method to identify joint fMRI-fPET brain activations in response to a visual stimulation task. The mcICA method produces a fused map from the multimodal datasets with equal contributions of information from both modalities, measured by entropy. We validated the method in silico, and applied it to an in vivo visual stimulation experiment. The mcICA method estimated the activated brain regions in the visual cortex modulated by both BOLD and FDG signals. The mcICA provides a fully data-driven analysis approach to analyze cerebral haemodynamic response and glucose uptake signals arising from exogenously induced neuronal activity.

中文翻译：

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使用多模态串联 ICA (mcICA) 方法估计同时的 BOLD 和动态 FDG 代谢脑激活

同时进行的磁共振和正电子发射断层扫描提供了一个机会，可以在一次扫描中测量大脑血流动力学和新陈代谢，并从多模式测量中识别大脑对外部刺激的反应。然而，可用于联合分析同时获得的血氧水平依赖性功能 MRI (fMRI) 和 18-F-氟脱氧葡萄糖功能 PET (fPET) 数据集的分析方法很少。在这项工作中，我们提出了一种新的多模态串联 ICA (mcICA) 方法来识别联合 fMRI-fPET 大脑激活以响应视觉刺激任务。mcICA 方法从多模态数据集生成融合图，两种模态的信息贡献相等，由熵测量。我们在计算机上验证了该方法，并将其应用于体内视觉刺激实验。mcICA 方法估计了由 BOLD 和 FDG 信号调制的视觉皮层中激活的大脑区域。mcICA 提供了一种完全数据驱动的分析方法来分析由外源性诱导的神经元活动引起的脑血流动力学反应和葡萄糖摄取信号。